Advanced Deep Learning with TensorFlow 2 and Keras: Apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more, 2nd Edition

 
9781838821654: Advanced Deep Learning with TensorFlow 2 and Keras: Apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more, 2nd Edition
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Rowel Atienza
Published by Packt Publishing Limited, United Kingdom (2020)
ISBN 10: 1838821651 ISBN 13: 9781838821654
New Paperback Quantity Available: 10
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The Book Depository
(London, United Kingdom)

Book Description Packt Publishing Limited, United Kingdom, 2020. Paperback. Condition: New. Language: English. Brand new Book. Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and KerasKey FeaturesExplore the most advanced deep learning techniques that drive modern AI resultsNew coverage of unsupervised deep learning using mutual information, object detection, and semantic segmentationCompletely updated for TensorFlow 2.xBook DescriptionAdvanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet), further allowing you to create your own cutting-edge AI ing Keras as an open-source deep learning library, the book features hands-on projects that show you how to create more effective AI with the most up-to-date techniques.Starting with an overview of multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the book then introduces more cutting-edge techniques as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You will then learn about GANs, and how they can unlock new levels of AI performance.Next, you'll discover how a variational autoencoder (VAE) is implemented, and how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans. You'll also learn to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.What you will learnUse mutual information maximization techniques to perform unsupervised learningUse segmentation to identify the pixel-wise class of each object in an imageIdentify both the bounding box and class of objects in an image using object detectionLearn the building blocks for advanced techniques - MLPss, CNN, and RNNsUnderstand deep neural networks - including ResNet and DenseNetUnderstand and build autoregressive models - autoencoders, VAEs, and GANsDiscover and implement deep reinforcement learning methodsWho this book is forThis is not an introductory book, so fluency with Python is required. The reader should also be familiar with some machine learning approaches, and practical experience with DL will also be helpful. Knowledge of Keras or TensorFlow 2.0 is not required but is recommended. Seller Inventory # AAV9781838821654

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2.

Rowel Atienza
Published by Packt Publishing Limited, United Kingdom (2020)
ISBN 10: 1838821651 ISBN 13: 9781838821654
New Paperback Quantity Available: 10
Seller:
Book Depository International
(London, United Kingdom)

Book Description Packt Publishing Limited, United Kingdom, 2020. Paperback. Condition: New. Language: English. Brand new Book. Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and KerasKey FeaturesExplore the most advanced deep learning techniques that drive modern AI resultsNew coverage of unsupervised deep learning using mutual information, object detection, and semantic segmentationCompletely updated for TensorFlow 2.xBook DescriptionAdvanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet), further allowing you to create your own cutting-edge AI ing Keras as an open-source deep learning library, the book features hands-on projects that show you how to create more effective AI with the most up-to-date techniques.Starting with an overview of multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the book then introduces more cutting-edge techniques as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You will then learn about GANs, and how they can unlock new levels of AI performance.Next, you'll discover how a variational autoencoder (VAE) is implemented, and how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans. You'll also learn to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.What you will learnUse mutual information maximization techniques to perform unsupervised learningUse segmentation to identify the pixel-wise class of each object in an imageIdentify both the bounding box and class of objects in an image using object detectionLearn the building blocks for advanced techniques - MLPss, CNN, and RNNsUnderstand deep neural networks - including ResNet and DenseNetUnderstand and build autoregressive models - autoencoders, VAEs, and GANsDiscover and implement deep reinforcement learning methodsWho this book is forThis is not an introductory book, so fluency with Python is required. The reader should also be familiar with some machine learning approaches, and practical experience with DL will also be helpful. Knowledge of Keras or TensorFlow 2.0 is not required but is recommended. Seller Inventory # AAV9781838821654

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Atienza, Rowel
Published by Packt Publishing 2/28/2020 (2020)
ISBN 10: 1838821651 ISBN 13: 9781838821654
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BargainBookStores
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Book Description Packt Publishing 2/28/2020, 2020. Paperback or Softback. Condition: New. Advanced Deep Learning with TensorFlow 2 and Keras - Second Edition. Book. Seller Inventory # BBS-9781838821654

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Rowel Atienza
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Book Description Packt Publishing Limited, 2020. PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # LQ-9781838821654

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Atienza, Rowel
ISBN 10: 1838821651 ISBN 13: 9781838821654
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Rowel Atienza
Published by Packt Publishing Limited (2020)
ISBN 10: 1838821651 ISBN 13: 9781838821654
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Book Description Packt Publishing Limited, 2020. PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # LQ-9781838821654

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Atienza, Rowel
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Rowel Atienza
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